Camera systems are increasingly employed in the printing industry in connection with various applications, such as, for example, in inspection systems, in path monitoring systems or in registration measuring systems. These systems are typically arranged for use with a printing press or with a machine which processes material to be imprinted. Moreover, there is a requirement that these systems should perform their functions “in-line”, integrated into the working process of the printing press or of the machine processing material to be imprinted. This “in-line” requirement presents a considerable challenge to the respective camera system because of the large amount of data provided by the camera system and because of the rapid process speed of the printing press or of the machine processing the material to be imprinted. It is difficult, for example, to obtain a dependable evaluation, preferably of each identifying characteristic, and even of identifying characteristics which are difficult to identify by spectral photometry, in spite of the high transport speed of the material, during the short time available for making an evaluation in the course of a quality control. Electronic image sensors (are often used in such camera systems for recording images. In particular, these systems often use color cameras with an image sensor consisting of a CCDchip, whose light-sensitive pixels provide an output signal, usually, for example, in three separate signal channels, primarily for the colors red, green and blue, that are corresponding to the color recorded in the observed range.
A problem that exists with known camera systems in connection with testing colored material, and in particular with testing material imprinted in colors, consists in that the image data provided by the color cameras often do no correspond to the color perception of the human eye. Unprocessed image data received from these color cameras are often insufficient with respect to color balance, brightness, contrast and color tone reproduction with respect to the color match corresponding to the human color perception. The main reason for this problem, besides the insufficiencies of lenses and illumination devices, is the spectral sensitivity distribution of the color cameras which are employed. If the sensitivity distributions of the color cameras employed does not match the sensitivity distribution of the human eye. The result is that, in the course of subsequent further processing, for example when the image data is displayed on a color monitor, the image data provided by the color cameras lead to a false visual impression. During checking, a reasonable qualitative evaluation of the imprinted material is hardly possible for this reason alone.
As a result of previous production processes, it can occur that the position of a detection characteristic to be evaluated during the checking process varies within certain tolerance limits in a defined expected range. For example, the position of a window thread, such as is used, for example, in connection with bills or with stamps, in relation to the print image of the bills or stamps on a printed sheet, can vary because of the properties of the production process for producing the window thread. Such acceptable position deviations of certain identifying characteristics can generate a malfunction report in inspection systems, since a print pattern defined as a reference value is compared sequentially, print position by print position, with the actual printed image. The result is that deviations in the position of identifying characteristics are detected as errors, although they are, in fact, not errors.
For example, a method is known from DE 196 13 082 A2, wherein an imprinted material, such as, for example, a print sheet imprinted with bills and provided with a silver thread, hologram or kinegram, is illuminated by an illuminating device in such a way that the light reflected by the imprinted material enters a photoelectric sensor. The image taken by the photoelectric sensor can thereafter be evaluated in an evaluating device, such as, for example, in a standard computer provided with suitable evaluation software, and can be checked for printing errors. However, in this case, it is a requirement, for conducting the evaluation, that an identifying characteristic, whose position varies, have a sufficiently high reflecting capability, if, for example, it is embodied as a shiny silver thread. Accordingly, it is disadvantageous that, after having been recorded by the use of the photoelectric sensor, that identifying characteristics, whose image properties do not differ sufficiently strongly from the image properties of the remaining print image, such as is the case with, for example, colored window threads, cannot be detected by the evaluation device with sufficient reliability.
A method for the qualitative evaluation of a material with at least one identifying characteristic is known from DE 101 32 589 A1. An image of the material to be evaluated is recorded by an image sensor. The geometric contours and/or the relative arrangement of several identifying characteristics of this image are evaluated, with respect to each other, in an evaluation device.
A method for signal evaluation of an electronic image sensor, in connection with detecting the patterns of image contents of a test body, is known from post-published DE 102 34 086 A1. A decision regarding the assignment of the test body to a defined class of test bodies is made.
A measuring arrangement for identifying valuable objects by digital image analysis is known from DE 198 02 781 A. A narrow-band excitation light source, such as, for example, a tunable laser, illuminates a selected location area of the object with light within a narrow frequency range. Light, which is reflected by the object, or an emission that is induced in the object because of its being exposed to radiation, is, for example, detected by a photometrically calibrated CCD camera having a multitude of pixels, is digitized and is forwarded to a computer in the form of a data set characterizing each pixel and is stored in a memory. The photographically detected object can also be additionally surveyed, so that information regarding a geometric arrangement of various objects, their distance from each other or the depth of their relief structure, can be added to the data set. The data set which is prepared from this image detection can be made available, for example via the internet, and can be used for a comparison of this data set with a data set prepared for another object, in order to check the other object at the different location for determining its agreement with the first object, i.e. the original object, and therefore to check its genuineness.
An arrangement for the classification of a pattern, in particular of a bill or a coin, is known from CH 684 222 A5. A multi-stage classification system, which is capable of learning, sequentially performs at least three tests on a pattern by comparing characteristic vectors with vectorial desired values. A light source illuminates the pattern and a sensor measures the radiation reflected by the pattern at discrete points in time.
Methods for pattern recognition customarily determine similarities such as, for example, distance measurements on segmented objects, or their calculated global threshold distributions. These methods are based on translation-invariant initial spectra. However, situations often occur in real life, such as by object displacements underneath the recording system, for example, by the existence of different backgrounds during the recordings, or because of aliasing effects, so that in many cases a direct comparison of these initial spectra with stored reference values cannot be performed.